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Record W4387457263 · doi:10.1242/jeb.246747

Dogfish heart rate peaks in warm water before they get agitated

2023· article· en· W4387457263 on OpenAlexaboutno aff
Jarren Kay

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
Fundersnot available
KeywordsFish <Actinopterygii>FisheryPredationTask (project management)BiologyEcologyEconomicsManagement

Abstract

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As climate change causes the world's waters to warm, many aquatic animals are finding themselves in new locations because, for many, moving away is the only viable option to cool down. If they stay in hot enough water, fish lose their ability to stay upright, leaving them unable to find prey and making them easy targets for predators. But what happens to fish before they can no longer stay upright? Generally, when the water gets too hot, fish get more agitated and look for a cooler place to stay. Ian Bouyoucos, Alyssa Weinrauch, Ken Jefferies and Gary Anderson of the University of Manitoba, Canada, think that there may be other signs – besides becoming agitated – that scientists could use to see if fish are stressed because of the temperature of the waters that they live in. To answer this question, the researchers turned to the pacific spiny dogfish (Squalus suckleyi) to help them.First, the team needed to find out what temperatures the sharks could withstand before they started showing signs of being unable to move properly. After putting the sharks in individual tanks and letting them recover from the move, the researchers slowly began increasing the temperature. The sharks started to become agitated at 23.2°C and started to show muscle spasms at 24.6°C, suggesting that this was the highest temperature that they could tolerate and still move. A week later, the team then began the arduous task of measuring the blood pressure of the sharks. After the sharks were fitted with blood pressure monitors, the researchers placed the dogfish in individual tanks before slowly warming up the water. Bouyoucos and colleagues were able to use the blood pressure measurements to estimate the shark's heart rate. As the water got hotter, the shark's heart rate more than doubled from ∼26 to ∼54 beats min−1, reaching this peak at 22.6°C; a temperature that is lower than both the maximum and the temperature at which they start getting agitated. This means that the warmer waters are affecting the dogfish before they start showing any outward signs. That then led to another question: are there any other signs that the sharks are stressed before they start becoming agitated?Bouyoucos and colleagues took blood and tissue samples from the sharks at their normal temperature and again at the temperature when their heart rate was at its highest. They found that levels of lactic acid increased in the blood and the pH inside the blood cells was decreased – both signs that the animal is stressed. Additionally, the team found that the levels of the enzyme citrate synthase were higher in the muscle. This enzyme increases when the mitochondria are needed to make more energy for the cells to use, suggesting that these dogfish require more energy to keep their body functioning. If the muscles and blood were showing signs of stress at this temperature, surely there must be something that tells the shark that the water is too hot to stay in.The researchers next turned to a protein called heat shock protein 70. The levels of this protein get higher when the animal is too hot in an attempt to protect the tissues. The team found that the RNA levels of this protein were higher in the gills, hearts and brain tissue of dogfish in warm waters. This suggests that these organs are extremely important for telling the animal when it's time to move to a new environment. This also gives scientists a new tool to use for determining how climate change will affect where species can live.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.277
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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